Sovereign AI Factory
Energy & Cooling for AI Factories: Carbon-Aligned Performance
Practical guide to energy and thermal design for modern AI clusters, covering liquid immersion cooling, direct-to-chip solutions, and renewable-aligned scheduling for Australian data centres.
By SCX.ai Infrastructure Team6 min read
Energy and thermal design dominate the OPEX of modern AI clusters. This article outlines practical options for liquid immersion and direct‑to‑chip cooling aligned to Australian renewable profiles, enabling low‑cost, high‑density AI compute.
Design Priorities
- Liquid immersion racks reach higher power densities with fewer failure points
- Direct‑to‑chip loops improve heat transfer and reduce fan energy draw
- Renewable‑aligned scheduling reduces cost and emissions without SLA impact
- Heat reuse to nearby facilities improves total efficiency
Australian Context
Regional energy mix and climatic conditions vary widely across states. Selecting data centres close to renewable hubs and implementing predictive load shaping yields a measurable cost‑per‑token advantage.
Key Takeaways
- Liquid cooling and renewable matching can reduce power costs by double‑digit percentages
- Thermal design is a first‑order factor for AI factory economics
- Deploy near renewable corridors to minimise grid congestion and egress costs